Context-aware cross-layer optimized video streaming in wireless multimedia sensor networks

The appearance of wireless multimedia sensor networks (WMSNs) requires a new generation transmission paradigm towards intelligent and ubiquitous communication. Video sensors are used in WMSNs to enhance the capability for event description. Multiple routing paths are often used for transmitting video streams. However, not every path found by multi-path routing algorithm is suitable for transmitting video, because a long routing path with a long end-to-end transmission delay may not satisfy the time constraint of the video. Furthermore, each video stream includes two kinds of information: image and audio streams. In different applications, image and audio streams play different roles, and the importance levels are different. Higher priority should be given to the more important stream (either the image stream or the audio stream) to guarantee the using of limited bandwidth and energy in WMSNs. In this paper, we propose a context-aware cross-layer optimized Multi-Path Multi-Priority (MPMP) transmission scheme, in which a Two-Phase geographic Greedy Forwarding (TPGF) multi-path routing protocol is used in network layer to explore the maximum number of node-disjoint routing paths, and a Context-Aware Multi-path Selection algorithm (CAMS) is used in transport layer to choose the maximum number of paths from all found node-disjoint routing paths for maximizing the gathering of the most valuable information to the base station. Simulation results show that the MPMP scheme can effectively maximize the gathering of the most valuable information and guarantee the end-to-end transmission delay.